Do you need to know math to do machine learning? Yes! The big 4 math disciplines that make up machine learning are linear algebra, probability theory, calculus, and statistics. I'm going to cover how each are used by going through a linear regression problem that predicts the price of an apartment in NYC based on its price per square foot. Then we'll switch over to a logistic regression model to change it up a bit. This will be a hands-on way to see how each of these disciplines are used in the field.
Code for this video (with coding challenge):
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https://towardsdatascience.com/the-mathematics-of-machine-learning-894f046c568
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https://www.quora.com/How-do-I-learn-mathematics-for-machine-learning
https://courses.washington.edu/css490/2012.Winter/lecture_slides/02_math_essentials.pdf
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So we've talked a lot in this series about how computers fetch and display data, but how do they make decisions on this data? From spam filters and self-driving cars, to cutting edge medical diagnosis and real-time language translation, there has been an increasing need for our computers to learn from data and apply that knowledge to make predictions and decisions. This is the heart of machine learning which sits inside the more ambitious goal of artificial intelligence. We may be a long way from self-aware computers that think just like us, but with advancements in deep learning and artificial neural networks our computers are becoming more powerful than ever.
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Decision Tree (CART) - Machine Learning Fun and Easy
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Decision tree is a type of supervised learning algorithm (having a pre-defined target variable) that is mostly used in classification problems. A tree has many analogies in real life, and turns out that it has influenced a wide area of machine learning, covering both classification and regression (CART).
So a decision tree is a flow-chart-like structure, where each internal node denotes a test on an attribute, each branch represents the outcome of a test, and each leaf (or terminal) node holds a class label. The topmost node in a tree is the root node.
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View full lesson: http://ed.ted.com/lessons/the-magic-of-vedic-math-gaurav-tekriwal
There is more than one way to reach a correct answer in mathematics. Vedic math, an ancient Indian method, sidesteps traditional computations in a manner that provides a shortcut, while being fun to use and to learn. At TEDYouth 2012, to ooh's and aah's from the amazed crowd, Gaurav Tekriwal demonstrates the magic of Vedic math.
Talk by Gaurav Tekriwal.

Can we predict the outcome of a football game given a dataset of past games? That's the question that we'll answer in this episode by using the scikit-learn machine learning library as our predictive tool.
Code for this video:
https://github.com/llSourcell/Predicting_Winning_Teams
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More learning resources:
https://arxiv.org/pdf/1511.05837.pdf
https://doctorspin.me/digital-strategy/machine-learning/
https://dashee87.github.io/football/python/predicting-football-results-with-statistical-modelling/
http://data-informed.com/predict-winners-big-games-machine-learning/
https://github.com/ihaque/fantasy
https://www.credera.com/blog/business-intelligence/using-machine-learning-predict-nfl-games/
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SUPER EXCITING to be a QUANT in 2019
If, in early 2019, you are contemplating going into quantitative finance, then keep contemplating. You’re unquestionably on the right track.
“Its super-exciting to be a quant in 2019”
Quants’ enthusiasm for being quants might be dismissed as self-love.
But isn’t that justified, well, let’s see, we are seeing a trend where every firm wants people with IT skills and these people on the buy side and the sell side are known as quants or strats and they do not come cheap, not only are they good at IT skills but also excellent at researching.
The demand for quants is being driven by the, explosion of alternative data. Both hedge funds and banks are mining datasets looking for an edge. It's become standard to have a data factory and you need the big data expertise to manage it. There are now a lot of IT people and quants just managing the stats.
The upshot is that trading floors which were becoming devoid of humans are being repopulated. “Ten years ago, you had trading floors filled with people,” “Then you had trading floors filled with machines, and then today we’re back to having a lot of people again – except the people are now an army of quants looking at data.
There are no stats for quant employment globally, but all the global banks, asset managers, hedge funds as well as global tech firms run internship programs which is a good entry point.
In the next few years, demand for quants has the potential to increase further as more fixed income trades are placed electronically. On fixed income trading floors, quants have yet to proliferate to the same extent, but this will change with electronification and the related increase in trading data.
“On an equities trading floor nowadays, you might find 10 traders and 90 quants,” These firms will have more and more people with a quantitative background working in sales and trading, They may not have a PhD, but this trend is going to accelerate massively.
Unfortunately this does not mean that you can walk into a quant job. Normally, Banks and funds are inundated with high quality CVs as up to 200 people a week apply. Most of the successful candidates have PhDs and are creative, they have original ideas on how to analyze and apply data.
If you're watching this video, you might be inclined to rush out and get a quantitative qualification. However, the bad news is that quants time in the sun may be fleeting.
Just as traders and brokers were displaced by algorithms and electronic trading systems, so human quants stand to be displaced by machine learning programs.
The good news is that there's little sign of this so far. Machine learning [to drive investments] is a huge bubble its been around since 1992 and the return on investment is poor...The most useful thing for quant funds is the opportunity to use alternative data.
If you like the video then click the like button, subscribe the channel and share it with your friends if you feel its useful. You can also comment your views and share some insights regarding the same. Hope to see you again next week, same time and same place till then ciao.
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Evolutionary/genetic algorithms are somewhat of a mystery to many in the machine learning discipline. You don't see papers regularly published using them but they are a really fascinating subfield and in this video, we're going to use a genetic algorithm to improve invaders in a space invaders game!
Code for this video:
https://github.com/llSourcell/Evolutionary_Space_Invaders
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http://www.obitko.com/tutorials/genetic-algorithms/
http://www-cs-students.stanford.edu/~jl/Essays/ga.html
http://www.alanzucconi.com/2016/04/06/evolutionary-coputation-1/
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( R Training : https://www.edureka.co/r-for-analytics )
This Edureka R Tutorial (R Tutorial Blog: https://goo.gl/mia382) will help you in understanding the fundamentals of R tool and help you build a strong foundation in R. Below are the topics covered in this tutorial:
1. Why do we need Analytics ?
2. What is Business Analytics ?
3. Why R ?
4. Variables in R
5. Data Operator
6. Data Types
7. Flow Control
8. Plotting a graph in R
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How it Works?
1. This is a 5 Week Instructor led Online Course, 30 hours of assignment and 20 hours of project work
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate!
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About the Course
edureka's Data Analytics with R training course is specially designed to provide the requisite knowledge and skills to become a successful analytics professional. It covers concepts of Data Manipulation, Exploratory Data Analysis, etc before moving over to advanced topics like the Ensemble of Decision trees, Collaborative filtering, etc. During our Data Analytics with R Certification training, our instructors will help you:
1. Understand concepts around Business Intelligence and Business Analytics
2. Explore Recommendation Systems with functions like Association Rule Mining , user-based collaborative filtering and Item-based collaborative filtering among others
3. Apply various supervised machine learning techniques
4. Perform Analysis of Variance (ANOVA)
5. Learn where to use algorithms - Decision Trees, Logistic Regression, Support Vector Machines, Ensemble Techniques etc
6. Use various packages in R to create fancy plots
7. Work on a real-life project, implementing supervised and unsupervised machine learning techniques to derive business insights
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Who should go for this course?
This course is meant for all those students and professionals who are interested in working in analytics industry and are keen to enhance their technical skills with exposure to cutting-edge practices. This is a great course for all those who are ambitious to become 'Data Analysts' in near future. This is a must learn course for professionals from Mathematics, Statistics or Economics background and interested in learning Business Analytics.
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Why learn Data Analytics with R?
The Data Analytics with R training certifies you in mastering the most popular Analytics tool. "R" wins on Statistical Capability, Graphical capability, Cost, rich set of packages and is the most preferred tool for Data Scientists.
Below is a blog that will help you understand the significance of R and Data Science: Mastering R Is The First Step For A Top-Class Data Science Career
Having Data Science skills is a highly preferred learning path after the Data Analytics with R training. Check out the upgraded Data Science Course
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This is the Official Video of Parents and Teachers Town Hall Meeting November 6th, 2013, This Video is 1hr 45min... This edited version has the background of the panelists edited out with the intent to speed up the important discussions.
This meeting was called by Concerned Parents and Teachers in the Conejo Valley School District of California. Those present have noticed an unhealthy change in education reform that is directly affecting the rights of parents and their children. Parents are not being given full disclosure of the new "Assessments" and "Surveys" in public education. This video is to educate every parent of their legal rights in education and how to safely "opt their child out" of these "Assessments and Surveys" without putting their child's education at risk.
Please click on the following links to the Concerned Parents website to download the "opt out form" along with all the other forms and documents presented in this video.
http://www.ConcernedParentsOfCalifornia.com
http://www.ConcernedParentsOfConejoValley.com
http://www.pji.org
http://www.hslda.org (for a good history lesson on CommonCore. check out their Building the Machine Movie.)
***Disclaimer****
(This site will not be making money off the video or from advertisements as was promised on the video release forms.)
Los Angeles - Angelinos are heavily misrepresented and the Teachers Union is running scared. Please like this video and spread the news to parents and students across the nation to help them learn about their rights and protections they desperately need in education!

In which John Green teaches you about the European Renaissance. European learning changed the world in the 15th and 16th century, but was it a cultural revolution, or an evolution? We'd argue that any cultural shift that occurs over a couple of hundred years isn't too overwhelming to the people who live through it. In retrospect though, the cultural bloom in Europe during this time was pretty impressive. In addition to investigating what caused the Renaissance and who benefitted from the changes that occurred, John will tell you just how the Ninja Turtles got mixed up in all this.
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What is a blockchain and how do they work? I'll explain why blockchains are so special in simple and plain English!
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In this video I explain very briefly how the Random Forest algorithm works with a simple example composed by 4 decision trees.
The presentation is available at:
https://prezi.com/905bwnaa7dva/?utm_campaign=share&utm_medium=copy

Machine learning and Data Mining sure sound like complicated things, but that isn't always the case. Here we talk about the surprisingly simple and surprisingly effective K-nearest neighbors algorithm.
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A webcast led by Karen Hsu of Datameer.
Surveys reveal that concerns about data quality can create barriers for companies deploying Analytics and BI initiatives. How can you readily identify and correct data quality issues at every step of your big data analysis to ensure accurate insights into customer behavior? In this webcast, we'll discuss how IT and business users can leverage self-service visualizations to quickly spot and correct data anomalies throughout the analytic process.
You will learn how to:
- Continuously visualize a profile of your data to identify inconsistencies, incompleteness and duplicates in your data
- Visualize machine learning and data mining, including clustering, decision tree analysis, column correlations and recommendations
- Create self-service visualizations for business and IT users
About Karen Hsu:
Karen is Senior Director, Product Marketing at Datameer. With over 15 years of experience in enterprise software, Karen Hsu has co-authored 4 patents and worked in a variety of engineering, marketing and sales roles.
Most recently she came from Informatica where she worked with the start-ups Informatica purchased to bring big data, data quality, master data management, B2B and data security solutions to market.
Karen has a Bachelors of Science degree in Management Science and Engineering from Stanford University.
@Karenhsumar
About host Ben Lorica:
Ben Lorica is the Chief Data Scientist at O'Reilly Media, Inc. He has applied Business Intelligence, Data Mining, Machine Learning and Statistical Analysis in a variety of settings including Direct Marketing, Consumer and Market Research, Targeted Advertising, Text Mining, and Financial Engineering. His background includes stints with an investment management company, internet startups, and financial services.
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In this video I describe how the k Nearest Neighbors algorithm works, and provide a simple example using 2-dimensional data and k = 3.
This presentation is available at: http://prezi.com/ukps8hzjizqw/?utm_campaign=share&utm_medium=copy

To unleash the potential of all learners, we need to start looking at what people can do, not just what they can say. "Many of The cognitive differences of neurodiverse students (learners with Autism, ADD, Dyslexia and other cognitive functions that make school difficult) may also empower them with creativity, resilience, and innovative approaches to problem-solving.
-Our education system struggles to measure and support these different ways of thinking, denying diverse learners their optimal learning opportunities and robbing Our future workforce of The talent and ingenuity that diverse learners offer.
-digital environments—including games, augmented, virtual and mixed reality—offer new ways to measure learners’ implicit knowledge, not relying on a test. games have The “stickiness” that motivate diverse learners to drill deeper, pursue new challenges, and persist to solve problems.
-digital environments generate data logs and educational data mining models---algorithms that identify common patterns of behavior to see where each learner struggles and succeeds in a digital experience--- can inform teachers and designers How to customize learning experience for each and every learner." Dr. Jodi Asbell-Clarke is the co-founder and co-director of the Educational Gaming Environments Group (EdGE) at TERC. TERC is a non-profit research and development organization focusing on innovative, technology-based STEM education. Jodi and the EdGE team of game designers, educators, and researchers study implicit STEM learning in digital games to transform science education.
A believer in Seymore Papert’s term ‘hard fun’, EdGE applies it to education by designing challenging free-choice STEM learning games that are within the grasp of the player motivating them to keep playing and learn advanced science content in their free time. EdGE researchers also use educational data mining to measure implicit learning in games, and work with educators to understand how it can be leveraged to measure classroom learning of related STEM content. EdGE is currently researching how AR and VR can enhance learning, especially for learners with particular skills and challenges, such as ADHD and autism.
Before joining TERC, Jodi dreamed of being an astronaut and went to Houston where she was an onboard software verification analyst for IBM during the first 25 space shuttle missions. She also taught Physics and Astrophysics to some of the brightest students in the country at the laboratory school at University of Illinois. Jodi’s academic background includes an MA in Math, an MSc in Astrophysics, and a PhD in Education. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx

Erin Raasch joins Jack Roeser and Carol Parisi to discuss.... Whats the Score with Common Core???
Common Core is a controversial set of untested educational standards that were snuck into cash-strapped Illinois as part of a competition for Obama stimulus money. By adopting Common Core, control of our schools was taken from our local school boards and parents and given to the dictates of a complex maze of agencies and corporations. In addition, schools are now required to collect and share personal data children as young as preschool all the way through to young adulthood in the workplace. Among other uses for this data, children will be the subject to high tech social science research and testing.
Erin Raasch is a wife and the mother of an 8 year old son who is enrolled in public school. Erin graduated from the University of Illinois and has a background in social science research and marketing. She is a constitutional conservative leader who is currently the social media coordinator for West Suburban Patriots, webmaster for IllinoisTeaParty.net and StopCommonCoreIllinois.org. She is also a FreedomWorks Illinois Activist and a public speaker.
To get more information about Common Core and what you can do to stop it please visit our website StopCommonCoreIllinois.org or join the conversation on Facebook at Stop Common Core in Illinois.
www.championnews.net

A self-driving car has a split second to decide whether to turn into oncoming traffic or hit a child who has lost control of her bicycle. An autonomous drone needs to decide whether to risk the lives of busload of civilians or lose a long-sought terrorist. How does a machine make an ethical decision? Can it “learn” to choose in situations that would strain human decision making? Can morality be programmed? We will tackle these questions and more as the leading AI experts, roboticists, neuroscientists, and legal experts debate the ethics and morality of thinking machines.
This program is part of the Big Ideas Series, made possible with support from the John Templeton Foundation.
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Original Program Date: June 4, 2016
MODERATOR: Bill Blakemore
PARTICIPANTS: Fernando Diaz, Colonel Linell Letendre, Gary Marcus, Matthias Scheutz, Wendell Wallach
Can Life and Death Decisions Be Coded? 00:06
Siri... What is the meaning of life? 1:49
Participant introductions 4:01
Asimov's Three Laws of Robotics 6:22
In 1966 ELIZA was one of the first artificial intelligence systems. 10:20
What is ALPHAGO? 15:43
TAY Tweets the first AI twitter bot. 19:25
Can you test learning Systems? 26:31
Robots and automatic reasoning demonstration 30:31
How do driverless cars work? 39:32
What is the trolley problem? 49:00
What is autonomy in military terms? 56:40
Are landmines the first automated weapon? 1:10:30
Defining how artificial intelligence learns 1:16:03
Using Minecraft to teach AI about humans and their interactions 1:22:27
Should we be afraid that AI will take over the world? 1:25:08

What's actually happening to a neural network as it learns?
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The following video is sort of an appendix to this one. The main goal with the follow-on video is to show the connection between the visual walkthrough here, and the representation of these "nudges" in terms of partial derivatives that you will find when reading about backpropagation in other resources, like Michael Nielsen's book or Chis Olah's blog.

According to data from researchers at the University of California in Santa Barbara,mercury left over from gold mining operations could poison the ecosystem for up to 10 thousand years into the future.
According to data from researchers at the University of California in Santa Barbara, mercury left over from gold mining operations could poison the ecosystem for up to 10 thousand years into the future.
The California gold rush from 1848 to 1884 left behind river valleys filled with sediment contaminated with toxic mercury.
Miners used mercury to bind with gold while they were sifting through eroded earth looking for the precious metal.
Michael Singer, a geologist and hydrologist who studied the mercury levels in California said: "This is a big deal because at the moment, there's quite a bit of mercury contamination that's in the ecosystems of the San Francisco Bay and Sacramento Delta."
Fish in the polluted water are eaten by other animals, and the mercury levels accumulate and increase in toxicity up the food chain.
There is no easy solution to the problem of mercury pollution as it is difficult to extract, and is usually exposed when the 150 year old gold rush sediment is stirred up by periodic floods. Levels may also be increasing as gold mining operations continue in certain areas.

http://www.utahnsagainstcommoncore.com - This video shows a series of ELA books by Zaner-Bloser with a core theme that is not literature and writing. It is social justice activism for ages 6 and up. This video replaces a previous one to fix audio background noise and address inaccurate criticisms of the previous video.

This lecture discusses the distinction between "signal" and "noise" -- and important definition when working with large or complex datasets.
This video is part of an online course called "Simulate, understand, & visualize data like a data scientist." The course includes 3+ hours of video lectures, course readers, MATLAB and Python code, exercises, and solutions.
More info here: https://www.udemy.com/suv-data-mxc/?couponCode=DATA-MXC10

Over the most recent couple of months, I have had a few people get in touch with me about their energy for wandering into the universe of information science and utilizing Machine Learning (ML) methods to test factual regularities and assemble immaculate information driven items. Notwithstanding, I have watched that some really do not have the essential scientific instinct and structure to get valuable outcomes. This is the primary reason I chose to compose this blog entry. As of late, there has been an upsurge in the accessibility of some simple to-utilize machine and profound learning bundles, for example, scikit-learn, Weka, Tensorflow, R-caret and so forth. Machine Learning hypothesis is a field that crosses measurable, probabilistic, software engineering and algorithmic viewpoints emerging from gaining iteratively from information and finding shrouded experiences which can be utilized to fabricate smart applications. In spite of the massive conceivable outcomes of Machine and Deep Learning, an intensive numerical comprehension of a large portion of these procedures is vital for a decent handle of the internal workings of the calculations and getting great outcomes.

Background: Data mining methods are used in empirical software engineering research to predict, diagnose, and plan for various tasks during the software development process. Such prediction models enhance managerial decision making. All the techniques so far used product and process related metrics in building predictive models. Aims: Software is designed, implemented and tested by people. Therefore, it is important to gain insight about people�s thought processes and their problem solving skills in order to improve software quality. While solving problems during any phase of the Software Development Life Cycle (SDLC), software engineers employ some heuristics. These heuristics may result in �cognitive biases�, which are defined as patterned deviations of human thought from the laws of logic and mathematics. In this research, we focused on a specific cognitive bias called �confirmation bias�, which is defined as the tendency of people to seek evidence that verifies a hypothesis rather than seeking evidence to falsify a hypothesis. Method: We defined a methodology to quantify/measure confirmation biases of software engineers by inheriting theories from the grounded work in cognitive psychology literature. We have come up with a �confirmation bias metrics set�. Results: Our empirical results demonstrated that developers� confirmation biases have a significant impact on the defect proneness of software. We found that individuals who have been trained in logical reasoning and hypotheses testing techniques exhibit less confirmatory behavior. By using developers� confirmation bias metrics values as input, we built learning-based models to predict defective parts of software, in addition to building models that are learned from static code and churn metrics. The performance of defect prediction models built using only confirmation bias metrics was found to be comparable with the performance of the models that use static code and/or churn metrics. Conclusions: We believe that next generation of empirical research in software engineering will bring more value to practice through better understanding of developer characteristics. Tool support is also necessary to measure, store and analyze such characteristics.

IT ASSIGNMENT
DATA ANALYSIS REPORT OF THE HEALTH AND POPULATION STATISTICS OF EAST ASIAN AND PACIFIC COUNTRIES.
Assessment and Submission Details Marks: 30% of the Total Assessment for the Course Due Date: 11:59pm Friday, Week 12
Submit your assignment to Blackboard Task 2. Please follow the submission instructions on
Blackboard
The assignment will be marked out of a total of 100 marks and forms 30% of the total assessment for the course. ALL assignments will be checked for plagiarism by SafeAssign system provided by Blackboard automatically.
Assignment submission extensions will only be made using the official Faculty of Arts, Business and Law Guidelines.
Requests for an extension to an assignment MUST be made to the course coordinator prior to the date of submission and requests made on the day of submission or after the submission date will only be considered in exceptional circumstances.
Background
A research team planned to study the heath development of the world in the past 15 years. The team retrieved the dataset from World Bank (http://databank.worldbank.org) about Health and Population Statistics between 2001 and 2015.
Assignment Task
You are a member of the team, and need to perform data analysis on countries in the region of East Asia & Pacific.
The team has not set any specific goal for the analysis. Therefore, you have the freedom to explore the data, and dig out anything you feel interesting or significant.
You have been requested to prepare a data analysis report about your work and explain your findings. The potential audiences include other researchers, business representatives, and government agencies. They may have limited ICT or mathematical knowledge.
To prepare the report, please follow the following outline:
1. Introduction
2. Data Setup
3. Exploratory Data Analysis
Perform 3 one-variable analysis. Plot at least one graph for each variable. Explain why the selected graph is appropriate.
Perform 2 two-variable analysis. Plot at least one graph for each variable. Explain why the selected graph is appropriate
The analysis can be performed on all years and all countries, or on a subset of your interest.
4. Advanced Analysis
4.1 Clustering
Briefly explain the concept of clustering and k-means.
Try to do a clustering analysis to group countries according to some selected attributes.
4.2 Linear Regression
Briefly explain the concept of linear regression.
Try to do 2 linear regression analysis. Plot the learned models.
The analysis can be performed on all years and all countries, or on a subset of your interest.
5. Conclusion
6. Reflections
In this part, discuss any difficulties you had performing the analysis and how you solved those difficulties. Reflect on how the analysis process went for you, what you learnt, and what you might do differently next time.
Referencing
2 references for the explanation of Clustering and 2 for linear regression are required. These references should follow the Harvard method of referencing. Note that ALL references should be from journal articles, conference papers, technical papers or a recognized expert in the field. DO NOT use Wikipedia as a reference. The use of unqualified references will result in the deduction of marks.
Assignment Guidelines
This assignment will take a number of weeks to complete and will require a good understanding of data science and management for successful completion. It is imperative that students take heed of the following points in relation to doing this assignment:
1. Ensure that you clearly understand the requirements for the assignment – what has to be done and what are the deliverables.
2. If you do not understand any of the assignment requirements – Please ASK the course coordinator or your tutor.
3. Each time you work on any aspect of the assignment reread the assignment requirements to ensure that what is required is clearly understood.
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Jo Chopra McGowan is co-founder and executive director of Latika Roy Foundation. Named after Latika Roy, the foundation provides education and social services to children, disadvantaged by disability and poverty. McGowan supervises Karuna Vihar, Latika Vihar, three early intervention centres, a vocational training and resource centre of the foundation. An English literature graduate of the University of Massachusetts, a social activist and an avid photographer, McGowan moved to India 30 years ago after her marriage with Dr. Ravi Chopra, director of the People's Science Institute, Dehradun.
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TEDxNarimanPoint 2011 took place on Friday September 2nd, 2011 at Y.B. Chavan Auditorium.
At TEDxNarimanPoint ideas were shared by eminent speakers on ways to transform the educational landscape in India and beyond. The speakers came from varied backgrounds of being educators themselves, social entrepreneurs in the education sector, policy makers, leaders in CSR etc. to present a view of the concerted effort required to change the educational landscape of a country.
In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)

In this episode of Awake And Empowered TV The Mass Exodus To Home Schooling , Ethann Fox speaks with Dr. Duke Pesta on the Common Core public education program that is now the primary method of education in all 50 states of the United States and that is rapidly spreading to other parts of the world. Dr. Duke Pesta and Etannn discuss the involvement of the Bill and Melinda Gates Foundation and the other architects of Common Core, their motivations, and the move toward a more socialist society in the US. Other topics include the data mining aspects of common core, and links to corporate and pharmaceutical interests.
About Dr. Duke Pesta
Dr. Duke Pesta received his M.A. in Renaissance literature from John Carroll University and his Ph.D. in Shakespeare and Renaissance literature from Purdue University. He has taught at major research institutions and small liberal arts colleges, on a wide variety of subjects at the graduate and undergraduate level, including courses on Shakespeare, Renaissance literature, the Bible, Russian literature, Christian Apologetics, and C.S. Lewis.
He has been active in educational reform, and was instrumental in developing and implementing an elective Bible course that is currently available for public high school students in Texas. Dr. Pesta is an engaging and animated speaker, whose experiences as an educational reformer, university professor, high school teacher, and the administrator of an online home school curriculum uniquely qualify him to address the current state of education in our country. He speaks at home school conventions and educational conferences across the nation on topics including the necessity of homeschooling, the decline of morality and critical thinking in the public schools, and the myriad ways that the educational establishment indoctrinates students. He is currently in demand on the speaking circuit as one of America’s foremost authorities on the dangers of Common Core.
Dr. Pesta has delivered over 400 talks on Common Core in 40 states. He has been interviewed on radio and television over 1500 times, including places as diverse as the United Kingdom, China, Canada, and Mexico. He has spoken on the lecture circuit on subjects ranging from the Founding Fathers, to the Christian Apologetics of C. S. Lewis, to the history of educational reform, to the politicization of the study of history in our nation’s schools. He hosted a radio segment entitled Classical Gasp for public radio, which considered current events through the lens of historical precedent.
Awake and Empowered TV with Ethann Fox on CCN
As the energy of our planet is shifting and changing, many who are awakening have come to realize their world is quite different than they were taught and had imagined. Societal institutions, religious traditions and mainstream media focus on our physical reality, materialism and other negative aspects of our reality, blocking our spiritual connection to the Divine. To support an emerging shift of consciousness in the world, now more than ever, people are in need of real world tools, and inspiration to cause positive change and support a higher vibration. Awake and Empowered TV is the impetus for raising vibration and increasing awareness of the positive aspects of this transition and where we are headed as a global consciousness.
Join spiritual teacher and host, Ethann Fox every Saturday at 12 p.m. GMT, 7 p.m. EST to create a new view of your world. Explore all of the positive aspects of the evolutionary changes on our planet that are emerging right now, just beneath the surface of mainstream reality. Each week, Ethann brings you the pioneers of our time from around the globe who are on the forefront of the expansion of human consciousness in the areas of technology, health, spirituality and science.
Tune in each week to explore alternative perspectives that will enrich your life journey, increase your happiness and steadily move toward a more fulfilling life experience. Together we inspire each other to build a new community of thought, as we empower ourselves and each other to live at our collective highest potential.
About Ethann Fox
Ethann Fox is a spiritual teacher, energy healer, the founder of the Flower of Life Center for Human Evolution and the visionary behind the Awake and Empowered Expo. His background in the business and financial markets as a professional trader and business owner is coupled by over 20 years as an accomplished astrologer and numerologist. Walking both the spiritual and business worlds, Ethann’s experience has given him an unconventional view and approach to personal happiness and professional success, melding the two as one.
About Flower of Life: http://www.floweroflifecenter.org/
About the Awake and Empowered Expo:http://awakeandempoweredexpo.com/about
About an Energy Transfer: http://www.ethannfox.com/energy-transfer
See our line up of other incredible presenters: http://awakeandempoweredexpo.com/presenters

Mini
David Brockman on "What uncovering a massive academic fraud taught me about how academia needs to change". A bit of background
http://nymag.com/scienceofus/2015/05/how-a-grad-student-uncovered-a-huge-fraud.html
Here's what David will be presenting: https://drive.google.com/file/d/0B_Qj0otlErJqVlJtMUhTU3ZiRzQ
David's Bio:
David Broockman is an Assistant Professor of Political Economy at the Stanford Graduate School of Business. His research uses randomized controlled experiments to help understand public opinion, voter behavior, and political representation. His work on these topics has appeared in the American Journal of Political Science, Political Analysis, and other academic journals, and been discussed in the New York Times, Washington Post, and many other media outlets. David has also helped design hundreds of experiments for the field, the web, email, mobile, and mail in the academic, political, and private sectors, including with the Analyst Institute, CREDO, and Google.
Main Talk
Bob Poekert will present COOLCAT (https://cs.gmu.edu/~dbarbara/COOLCAT/coolcat.pdf) by Daniel Barbara, Julia Couto, and Yi Li.
From Bob "The paper presents an entity resolution algorithm based on minimizing entropy within clusters. Entity resolution (aka identity resolution aka categorical clustering) is a problem that comes up a lot in practice but which most people try to solve just by heuristics because they don't know that it's something that there's research on. This approach is pretty general (it applies to anything that you can represent as discrete field-value pairs), and the math isn't too overwhelming. Also I like the name."
Bob's Bio:
Bob (@bobpoekert) works at the intersection of data mining and databases at Factual, and got hooked on CS papers after reading the Kademlia paper in high school while trying to figure out how Kazaa worked. Bob also does weird stuff with image processing (@a_quilt_bot probably being the most popular example).
http://www.meetup.com/papers-we-love-too/events/220795976/

Executives and data scientists from Baidu, LinkedIn, and Foursquare discuss how to generate real value from Big Data, and the importance of business leaders developing a vision of how Big Data is used in their organization. Susan Athey, Professor of Economics at Stanford Graduate School of Business, moderated this panel on "Generating Value from Big Data and Analytics" with panelists Li Fan (Baidu), Simon Zhang (LinkedIn), and Tianhui Michael Li (Foursquare) at the fourth annual China 2.0 conference hosted by Stanford Graduate School of Business on October 3, 2013.
Learn more about the fourth annual China 2.0 conference: http://sprie.gsb.stanford.edu/docs/china20_2013
China 2.0 is an initiative of the Stanford Graduate School of Business focusing on innovation and entrepreneurship in China. Learn more: http://www.china2.org/

Erin Raasch joins Jack Roeser and Carol Parisi to discuss.... Whats the Score with Common Core???
Common Core is a controversial set of untested educational standards that were snuck into cash-strapped Illinois as part of a competition for Obama stimulus money. By adopting Common Core, control of our schools was taken from our local school boards and parents and given to the dictates of a complex maze of agencies and corporations. In addition, schools are now required to collect and share personal data children as young as preschool all the way through to young adulthood in the workplace. Among other uses for this data, children will be the subject to high tech social science research and testing.
Erin Raasch is a wife and the mother of an 8 year old son who is enrolled in public school. Erin graduated from the University of Illinois and has a background in social science research and marketing. She is a constitutional conservative leader who is currently the social media coordinator for West Suburban Patriots, webmaster for IllinoisTeaParty.net and StopCommonCoreIllinois.org. She is also a FreedomWorks Illinois Activist and a public speaker.
To get more information about Common Core and what you can do to stop it please visit our website StopCommonCoreIllinois.org or join the conversation on Facebook at Stop Common Core in Illinois.
www.championnews.net

Speaker(s): Jake Torcasso
As part of the launch of the Center for the Economics of Human Development, Jake Torcasso a Research Professional at CEHD, delivered the talk, "Forecasting With Panel Data Over the Life-Course."
Forecasting with Panel Data over the Life-Course, or, more simply, the Forecasting Project, is a study of the predictive power of early-life measures for later-life outcomes. The project makes use of data from the Carolina Abecedarian Project and the Perry Preschool Project as well as data collected on children of mothers in the National Longitudinal Survey of Youth (1979), and proceeds in three steps. First, we identify early predictors of adult outcomes and compare their predictive power across datasets and age of measurement; second, we develop a forecasting strategy, which considers uncertainty in the selection of predictors and functional form; and third, we implement the forecasting strategy and perform a cross-validation across the datasets. The first step involves a detailed analysis of the measures available across datasets. The measures must be both relevant predictors and comparable across the datasets. To date, we have focused on detailed information provided on home stimulation, parenting, and early measures of both character and cognition. We estimate linear and separable models of adult outcomes on each early measure at a specific age, conditioning on a set of background variables.
The mission of the Center is to advance knowledge that fosters human flourishing by identifying sources of disadvantage and promoting equality of opportunity.
The Center will produce empirical and theoretical research that integrates ideas and methods across the social and natural sciences to create rigorous evidence for public policy.
You can keep up-to-date with ongoing research on our website at http://www.cehd.uchicago.edu.

Join us for Common Core -- The Portsmouth Interviews, a 5-part series, in which Ann Marie Banfield interviews two professors who wrote some of the top Math and English/Language Arts K-12 standards in the United States, as well as two other highly regarded education researchers. The shows are 30 minutes each.
Please visit us at: http://stopcommmoncorenh.org.
Click here for the background of Ann Marie Banfield and our guests.
The shows cover the following topics:
Show 1: Background and introduction of Common Core. This is well worth watching even if you already know about Common Core.
Show 2: Common Core Math, featuring James Milgram, Professor Emeritus of Mathematics, Stanford University, and co-writer of the highly regarded California Math Standards.
Show 3: Common Core English/Language Arts, featuring Professor Sandra Stotsky, writer of the Massachusetts K-12 standards, regarded as top in the country.
Show 4: Focus is on the constant testing inherent in Common Core, as well as the collection and sharing of data being collected on our children and families related to Common Core.
Show 5: The cost of Common Core and a discussion about what parents can do about Common Core.

Erin Raasch joins Jack Roeser and Carol Parisi to discuss.... Whats the Score with Common Core???
Common Core is a controversial set of untested educational standards that were snuck into cash-strapped Illinois as part of a competition for Obama stimulus money. By adopting Common Core, control of our schools was taken from our local school boards and parents and given to the dictates of a complex maze of agencies and corporations. In addition, schools are now required to collect and share personal data children as young as preschool all the way through to young adulthood in the workplace. Among other uses for this data, children will be the subject to high tech social science research and testing.
Erin Raasch is a wife and the mother of an 8 year old son who is enrolled in public school. Erin graduated from the University of Illinois and has a background in social science research and marketing. She is a constitutional conservative leader who is currently the social media coordinator for West Suburban Patriots, webmaster for IllinoisTeaParty.net and StopCommonCoreIllinois.org. She is also a FreedomWorks Illinois Activist and a public speaker.
To get more information about Common Core and what you can do to stop it please visit our website StopCommonCoreIllinois.org or join the conversation on Facebook at Stop Common Core in Illinois.
www.championnews.net

(8 Dec 2009)
1. Wide of building ablaze
2. Rescue team at market, smoke
3. Wide of building on fire
4. Pan of rescue workers taking body on stretcher
5. Fire engine arriving at scene
6. Tilt-up of scene of first explosion showing rescue workers and security
7. Wide of scene with police standing and destroyed shops
8. Blood on ground
9. Wide of ambulances at scene, body on ground in background under white sheet
10. Police officers at scene
11. Damaged motorbike
12. SOUNDBITE (Urdu) Mohammad Ahmad, Eyewitness:
"Suddenly we heard the loud noise of an explosion. We were a quite far away from the scene, and we saw one man who fell down as he ran away. After a few seconds another blast happened and everywhere became dark before our eyes. Everybody was running around and we saw one dead body on the ground and one over there (eyewitness points to spot)."
13. Various of scene showing destroyed market
14. Various of rescue workers removing covered bodies from scene, putting them in ambulances
15. Wide exterior of Sheikh Zaid Hospital emergency department
16. Medical staff treating patient
17. Close of woman receiving treatment
18. Tilt up of woman receiving medical treatment
STORYLINE
Two synchronised, remote-controlled bombs ripped through a market popular with women in the eastern Pakistani city of Lahore on Monday, igniting a massive fire and killing at least 36 people, authorities said.
About 100 people were wounded in the attacks in Lahore, which were apparently timed to take place when the Moon Market was as its busiest.
Authorities initially said both bombs at the market were believed to be remote-controlled, but they later said a suicide bomber was suspected to have carried out at least one of them.
The bombs exploded, at both ends of the market, within 30 seconds of each other, leaving dozens of cars and shops ablaze late into the night.
Many of victims were women and children, including a dead 2-year-old, a police officer said.
Most of the militant attacks in recent weeks have been directed at security forces, though several have targeted crowded public spaces like markets, apparently to create public anger and increase pressure on the government to call a halt to the offensive.
More than 400 people have been killed since the beginning of October, including 105 in a Peshawar market frequented by women. That attack occurred while U.S. Secretary of State Hillary Clinton was visiting Pakistan.
The Taliban generally claim responsibility for those attacks killing security officers, but they do not acknowledge carrying out the attacks targeting civilians.
Government officials and security analysts say there is little doubt the militants are behind all the attacks.
Moon Market sells clothes and shoes and is especially popular with women and their children.
A top Lahore government official said there were more than 36 dead and 100 wounded.
Lahore is Pakistan's second largest city and is not far from the border with India.
It has been hit several times by militants over the past year, including an attack on the visiting Sri Lankan cricket team and several strikes against security installations.
The attacks have coincided with rising speculation over the future of President Asif Ali Zardari.
On Monday, the Supreme Court began examining the legality of an amnesty protecting him and 8,000 other officials from graft prosecution.
The amnesty expired last month, and judges must rule on whether to reopen corruption cases against them. Although
Zardari has immunity from prosecution as president, some experts say the court could now take up cases challenging his eligibility to run for office.
You can license this story through AP Archive: http://www.aparchive.com/metadata/youtube/d0660182f15be51e935893bb4c1bc8c9
Find out more about AP Archive: http://www.aparchive.com/HowWeWork

William Meyer is putting his award-winning aerospace research to work for Scattering Solutions, Inc. His company is leading the way in creating breakthrough solutions in light scattering, which include an innovative technology that applies to drug screening. Mathematica provides sophisticated data analysis that enables researchers to prescreen drugs and determine whether they merit going to costly clinical trials.
Meyer expects Mathematica to play an even bigger role in the company's future discoveries. He is currently working on an application to run all of his light-scattering technologies with Mathematica. When that is finalized, Meyer's team will be able to prescreen thousands of drugs in a fraction of the time it takes now.
For more Mathematica videos and screencasts, please visit:
http://www.wolfram.com/broadcast

Original video here: https://www.youtube.com/watch?v=jweQNDCe218
Link 1: NVLink on NVIDIA GeForce RTX 2080 & 2080 Ti in Windows 10
http://puget.systems/go/s_nvlink_win10
Link 2: NVLINK on RTX 2080 TensorFlow and Peer-to-Peer Performance with Linux
http://puget.systems/go/s_nvlink_linux
Link 3: "Optimizing Storage for Premiere Pro" video
https://www.youtube.com/watch?v=r7zI7MYSY_0
Link 4: All Puget Systems publications
http://puget.systems/go/s_publications
Link 5: Puget Systems Oil Immersion Cooling
http://puget.systems/go/s_immersion
Link 6: Thermal Paste Application Techniques
http://puget.systems/go/s_thermal_paste
Link 7: Estimating CPU Performance using Amdahls Law
http://puget.systems/go/s_amdhal
Click here if you're interested in subscribing: http://bit.ly/Subscribe2SED ⇊ Click below for more links! ⇊
HOW TO BUILD A COMPUTER
1. DON'T BUY THE MOST EXPENSIVE MACHINE.
2. RESEARCH ACTUAL BENCHMARK DATA
3. BUY HARDWARE BASED ON YOUR SOFTWARE APPLICATION
4. More cores doesn't mean it's better for you!
Side note: The fast rendering capability of this new machine actually let me eat dinner with my family on the first night I used it. This is incredibly important to me.
A special thank you to Puget Systems for allowing me to visit and for helping me
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
GET SMARTER SECTION
I asked Jon to put together the specs on the computer I spec'd out
https://www.pugetsystems.com/go/smarter
Amdahl's Law
https://en.wikipedia.org/wiki/Amdahl%...
Moore's Law
https://en.wikipedia.org/wiki/Moore%2...
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Tweet Ideas to me at:
http://twitter.com/smartereveryday
I'm "ilikerockets" on Snapchat.
Snap Code: http://i.imgur.com/7DGfEpR.png
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https://www.facebook.com/SmarterEveryDay
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http://www.reddit.com/r/smartereveryday
Ambiance and musicy things by: Gordon McGladdery did the outro music the video.
http://ashellinthepit.bandcamp.com/
The thought is it my efforts making videos will help educate the world as a whole, and one day generate enough revenue to pay for my kids college education. Until then if you appreciate what you've learned in this video and the effort that went in to it, please SHARE THE VIDEO!
If you REALLY liked it, feel free to pitch a few dollars Smarter Every Day by becoming a Patron.
http://www.patreon.com/smartereveryday
Warm Regards,
Destin

Forbes Magazine has named Daniela Witten, Associate Professor of Biostatistics and Statistics at the University of Washington to its 30 under 30 list. Professor Witten improves the statistical tools used in genetic research.
UW 360 hosted by Carolyn Douglas, looks at events, people and places at the University of Washington.
http://uwtv.org/uw360
http://uwtv.org

National Aboriginal Day (NAD) is celebrated every June 21st. NAD is a time for all Canadians to recognize the unique heritage, the diverse cultures and the outstanding contributions of First Nations, Inuit and Métis peoples.
For more information about Aboriginal Affairs and Northern Development Canada, please visit http://www.aadnc-aandc.gc.ca.
For more information about National Aboriginal day, please visit http://www.nad.gc.ca.
Read a transcript of this video on the AANDC web site: http://www.aadnc-aandc.gc.ca/eng/1100100013727/1100100013729

The Massachusetts Department of Elementary and Secondary Education created an Audio Deep Dive to explain the measure of student learning in the Candidate Assessment of Performance (CAP).
View MP4
http://www.doe.mass.edu/edprep/videos/MeasureStudentLearning.mp4

All videos on this channel are released free of copyrights. You may download, modify, distribute, and use them royalty free for anything you like, even in commercial applications. Attribution is not required.
If you liked what you saw, feel free to hit the 'subscribe' button and give us a 'like' too if you're feeling great.

Convened by the Robert J. Margolis, MD, Center for Health Policy at Duke University, the Second Annual Duke-Margolis Conference on Real-World Data and Evidence will bring together top experts and speakers to examine topics related to the use of real-world data (RWD) and evidence (RWE) in drug development and regulatory decision-making. Workshop sessions will highlight emerging takeaways from two working papers :
“Characterizing the Quality and Relevancy of RWD for Regulatory Purposes”, which will be released ahead of the event, examines the process and factors that should be considered while characterizing RWD quality and relevancy for regulatory purposes
“Meeting Regulatory Standards with Fit-For-Purpose RWE”, which is still in active development and will be informed by discussion at this event, focuses on the process for determining the regulatory acceptability of observational studies